The bar for success is rising in higher education. University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
Watch our webinar, 4 Steps to Building a Customer Satisfaction Engine. SurveyMonkey's Director of Customer Success, Jeffrey Coleman, will show you how to:
- Ask questions that yield actionable data
- Scale follow-up actions and improvements
- Analyze survey data and get key metrics
- Close the loop by turning data into action
With SAP In-Memory Computing, massive amounts of data can be queried and analyzed 3600 times faster than before -- turning questions into action and giving you insight you can act on immediately. Your competitors will still be pondering the numbers while you are making your next move. Discover this eBook to learn more.
Consistency and customer experience are key to quality and profitability in retail. Manual reporting processes can be unwieldy and time-consuming, but bringing together all compliance procedures under one digital platform means fast, consistent and easy-to-access performance data.
Using real-time insights into best practice improves the reporting of quality control, stock loss prevention, inspection processes, logistics and more – saving time, increasing efficiency and boosting customer satisfaction. Benefits include better branding through monitoring rollouts with uploaded photos and videos, protection against shrinkage through improved inspection processes and audits, and clearer visibility of issues which means a speedier response.
In this six-step guide, we aim to help you solve your data challenges to prepare for advanced analytics, cognitive computing, machine learning and the resulting benefits of AI. We’ll show you how to get your data house in order, scale beyond the proof of concept stage, and develop an agile approach to data management. By continually repeating the steps in this guide, you’ll sharpen your data and shape it into a truly transformational business asset. You’ll be able to overcome some of the most common business problems, and work toward making positive changes:
• Improve customer satisfaction
• Reduce equipment outages
• Increase marketing campaign ROI
• Minimize fraud loss
• Improve employee retention
• Increase accuracy for financial forecasts
Put simply, the aim of reporting is to translate or convert data into information. Reporting done well often prompts end-users to raise questions about the business. Analytics fills in the gap, answering the questions raised by reporting, thereby transforming data into insights. Read more to find out how analytics can go beyond reporting to provide actionable recommendations to improve business performance.
Wholly relevant and personalized customer service is no longer an optional preference, so much as an inevitable reality. Through the right data management technology, marketers can pave the way for their customers to reach the right ticket for their chosen journey, through the channels they prefer, in a way which means something to them in that particular moment.
Airlines don’t have to make use of beacon technology and IoT to begin uplifting their outreach, but should choose a solution which is ready as soon as they are, to plug into, embrace and deliver actions with a shifting landscape of consumer touchpoints.
Published By: Attunity
Published Date: Jan 14, 2019
This whitepaper explores how to automate your data lake pipeline to address common challenges including how to prevent data lakes from devolving into useless data swamps and how to deliver analytics-ready data via automation.
Read Increase Data Lake ROI with Streaming Data Pipelines to learn about:
• Common data lake origins and challenges including integrating diverse data from multiple data source platforms, including lakes on premises and in the cloud.
• Delivering real-time integration, with change data capture (CDC) technology that integrates live transactions with the data lake.
• Rethinking the data lake with multi-stage methodology, continuous data ingestion and merging processes that assemble a historical data store.
• Leveraging a scalable and autonomous streaming data pipeline to deliver analytics-ready data sets for better business insights.
Read this Attunity whitepaper now to get ahead on your data lake strategy in 2019.
Business intelligence analytics streamline the task of gathering critical data across the health care enterprise and turns it into readily accessible, actionable information. Health care business intelligence is a package of software and services that offers clarity on and control over the vast amount of data needed to successfully run a medical organization.
The data-driven organization is the new benchmark for success. Firms that harness data to dictate strategic and tactical decisions companywide make more informed business plans, better optimize operations, improve customer interactions, and provide competitive edge. To achieve these benefits, organizations increasingly see data refinement - transforming raw data from various sources into relevant and actionable information and delivering it through self - service access to any user who needs it - as the path toward success by helping break though immature processes and legacy systems. However, data refinement only functions as well as the strategies and approaches behind it. Organizations that do not understand the right way to embrace refinement will fail to catch up to competitors that have mastered the correct approach.
DevOps allows teams to effectively build, test, release, and respond to your software. But creating an agile, data-driven culture is easier said than done. Developer and devops teams struggle with lack of visibility into application monitoring tools and systems, accelerated time-to-market pressure, and increased complexity throughout the devops lifecycle process. As a Splunk customer, how are you using your machine data platform to adopt DevOps and optimize your application delivery pipeline?
Download your copy of Driving DevOps Success With Data to learn:
How machine data can optimize your application delivery
The four key capabilities DevOps teams must have to optimize speed and customer satisfaction
Sample metrics to measure your DevOps processes against
This paper explores why your business needs the latest operational decision management (ODM) solutions to help turn data insights into action. Discover how IBM Operational Decision Manager software and the IBM Business Process Manager platform work together.
This paper explores why your business needs the latest operational decision management (ODM) solutions to help turn data insights into action. Discover how IBM Operational Decision Manager software and the IBM Business Process Manager platform work together to: *Recognize patterns that suggest opportunity or risk *Create and shape business events by automating decisions *Bring more dimension and precision to decision making by applying analytics to big data *Help you implement the right business processes by understanding data in context.
Your contact center is a hotbed of activity, constantly processing calls and emails, chats and social media posts, problems and solutions. As a result, it generates the kind of “big data” that other departments wish they had. But collecting that data is just the beginning. The next step is turning it into a plan of action.
The focus of modern business intelligence has been self-service; pushing data into the hands of end users more quickly with more accessible user interfaces so they can get answers fast and on their own. This has helped alleviate a major BI pain point: centralized, IT-dominated solutions have been too slow and too brittle to serve the business.
What has been masked is a lack of innovation in data modeling. Data modeling is a huge, valuable component of BI that has been largely neglected. In this webinar, we discuss Looker’s novel approach to data modeling and how it powers a data exploration environment with unprecedented depth and agility.
Topics covered include:
• A new architecture beyond direct connect
• Language-based, git-integrated data modeling
• Abstractions that make SQL more powerful and more efficient
IBM i2 Enterprise Insight Analysis helps analysts and investigators turn large data sets into comprehensive intelligence, in near real-time. With the help of advanced analytics and visual analysis capabilities, analysts can uncover hidden connections, patterns and trends buried in disparate data. Equip analysts and those on the front line with the tools they need to generate actionable intelligence, with mission critical speed.
Published By: Veritas
Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data.
In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
As organizations increasingly strive to become model-driven, they recognize the necessity of a data science platform. According to a recent survey report “Key Factors on the Journey to Become Model-Driven”, 86% of model-driven companies differentiate themselves by using a data science platform. And yet the question of whether to build or buy still remains.
This paper presents a framework to facilitate the decision process, and considers the four-year projection of total costs for both approaches in a sample scenario.
Read this whitepaper to understand three major factors in your decision process:
Total cost of ownership - Internal build costs often run into the tens of millions
Opportunity costs - Distraction from your core competency
Risk factors - Missed deadlines and delayed time to market
Data is the DNA of modern healthcare. As healthcare technology continues to evolve at a rapid pace, and patient data management and security evolve, emerging approaches for disease treatment and prevention—like precision medicine and healthcare content management—are becoming more necessary. Precision medicine is about moving from generic to more precise, population-focused diagnostics and treatment by factoring in data from patients’ genes, environment, lifestyle factors and family history, into clinical decision-making for earlier, more accurate diagnoses, and more effective treatment and prevention. Data is at the heart of enabling doctors and scientists to execute on this mission. Additionally, rapidly changing regulations throughout the world are affecting the management of all healthcare data. Infinidat removes data management barriers from this level of data interaction by removing isolated islands of storage and allowing much more data to reside on a single, high-performance, h
Published By: Workday
Published Date: Aug 07, 2018
From the rise of data analytics to new needs in budgeting, the shift to value-based medicine is bringing a fresh set of challenges to healthcare CFOs. How can you best meet these new demands and turn change into opportunity? This Becker’s Hospital Review eBook compiles 10 must-read articles that offer executive tips, actionable insights, and noteworthy trends for healthcare finance technology.
DatacenterDynamics is a brand of DCD Group, a global B2B media and publishing company that develops products to help senior professionals in the world's most ICT dependent organizations make risk-based infrastructure and capacity decisions.
Our portfolio of live events, online and print publishing, business intelligence and professional development brands are centred on the complexities of technology convergence. Operating in 42 different countries, we have developed a unique global knowledge and networking platform, which is trusted by over 30,000 ICT, engineering and technology professionals.
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